Translation and analysis of words by ChatGPT artificial intelligence
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lattice homomorphic - translation to russian
математика
решетчато гомоморфный
!['''Pic. 7:''' Non-lattice poset: <math>b</math> and <math>c</math> have common upper bounds <math>d, e,</math> and <math>f,</math> but none of them is the [[least upper bound]].](https://commons.wikimedia.org/wiki/Special:FilePath/NoLatticeDiagram.svg?width=200 "'''Pic. 7:''' Non-lattice poset: <math>b</math> and <math>c</math> have common upper bounds <math>d, e,</math> and <math>f,</math> but none of them is the [[least upper bound]].")
!['''Pic. 8:''' Non-lattice poset: <math>a</math> and <math>b</math> have common lower bounds <math>0, d, g, h,</math> and <math>i,</math> but none of them is the [[greatest lower bound]].](https://commons.wikimedia.org/wiki/Special:FilePath/Pow3nonlattice.svg?width=200 "'''Pic. 8:''' Non-lattice poset: <math>a</math> and <math>b</math> have common lower bounds <math>0, d, g, h,</math> and <math>i,</math> but none of them is the [[greatest lower bound]].")
!['''Pic. 1:''' Subsets of \{x, y, z\}, under [[set inclusion]]. The name "lattice" is suggested by the form of the [[Hasse diagram]] depicting it.](https://commons.wikimedia.org/wiki/Special:FilePath/Hasse diagram of powerset of 3.svg?width=200 "'''Pic. 1:''' Subsets of \{x, y, z\}, under [[set inclusion]]. The name \"lattice\" is suggested by the form of the [[Hasse diagram]] depicting it.")
![partition]]s of \{1, 2, 3, 4\}, ordered by "''refines''".](https://commons.wikimedia.org/wiki/Special:FilePath/Lattice of partitions of an order 4 set.svg?width=200 "partition]]s of \{1, 2, 3, 4\}, ordered by \"''refines''\".")
математика
гомоморфизм решеток
общая лексика
параметр решетки
Definition
Wikipedia
Homomorphic encryption is a form of encryption that allows computations to be performed on encrypted data without first having to decrypt it. The resulting computations are left in an encrypted form which, when decrypted, result in an output that is identical to that produced had the operations been performed on the unencrypted data. Homomorphic encryption can be used for privacy-preserving outsourced storage and computation. This allows data to be encrypted and out-sourced to commercial cloud environments for processing, all while encrypted.
For sensitive data, such as health care information, homomorphic encryption can be used to enable new services by removing privacy barriers inhibiting data sharing or increase security to existing services. For example, predictive analytics in health care can be hard to apply via a third party service provider due to medical data privacy concerns, but if the predictive analytics service provider can operate on encrypted data instead, these privacy concerns are diminished. Moreover, even if the service provider's system is compromised, the data would remain secure.
